This paper is to present a framework developed in order to
model and share knowledge within large organizations whether
they be private or public.
Called MIMIK (Method and Instruments for Modeling Integrated
Knowledge), it is based on a methodology,on eight different
models for graphical representation and on a knowledge-sharing
system.

Predictive analytics encompasses a variety of techniques from
statistics and data mining that analyze current and historical
data to make predictions about future events. Such predictions
rarely take the form of absolute statements, and are more
likely to be expressed as values that correspond to the odds
of a particular event or behavior taking place in the future.

Over the last ten years or so, face recognition has become
a popular area of research in computer vision and one of the
most successful applications of image analysis and understanding.
This site provides relevant information in the the area of
face recognition / Information pool for the face recognition
community / Entry point for novices as well as a centralized
information resource.

Heaton Research introduced two new online video-based courses
today. The Introduction to Neural Networks for Java and Introduction
to Neural Networks for C# courses are now open for enrollment.
These courses are offered free to the public. Programming
experience in Java or C# is suggested. These courses are taught
by Jeff Heaton, an artificial intelligence researcher and
former college instructor. The courses are presented in fifteen
weekly units consisting of a 20-30 minute video supplemented
with additional materials, assignments, and an online forum.

The goal of the FACETS
(Fast Analog Computing with Emergent Transient States) project
is to create a theoretical and experimental foundation for
the realisation of novel computing paradigms which exploit
the concepts experimentally observed in biological nervous
systems. The continuous interaction and scientific exchange
between biological experiments, computer modelling and hardware
emulations within the project provides a unique research infrastructure
that will in turn provide an improved insight into the computing
principles of the brain. This insight may potentially contribute
to an improved understanding of mental disorders in the human
brain and help to develop remedies.

The International Neural Network Society (INNS) is the premiere
organization for individuals interested in a theoretical and computational
understanding of the brain and applying that knowledge to develop
new and more effective forms of machine intelligence.

This site includes a series of exercises and demos. Each exercise
consists of a short introduction, a small demonstration program
written in Java (Java Applet), and a series of questions which
are intended as an invitation to play with the programs and explore
the possibilities of different algorithms.

Jay Scott resources site for Machine Learning for Gaming.
He describes game programs and their workings; they rely
on heuristic search algorithms, neural networks, genetic
algorithms, temporal differences, and other methods.

New research in artificial intelligence could lay the groundwork
for computer systems that learn from their users and the
world around them. Artificial intelligence, a field that
has tantalized social scientists and high-tech researchers
since the dawn of the computer industry, had lost its sex
appeal by the start of the last decade.
Now a new generation of researchers hopes to rekindle interest
in AI. Faster and cheaper computer processing power, memory,
and storage, and the rise of statistical techniques for
analyzing speech, handwriting, and the structure of written
texts, are helping spur new developments, as is the willingness
of today's practitioners to trade perfection for practical
solutions to everyday problems.

Programming Neural Networks in Java will show the intermediate
to advanced Java programmer how to create neural networks.
This book attempts to teach neural network programming through
two mechanisms. First the reader is shown how to create
a reusable neural network package that could be used in
any Java program. Second, this reusable neural network package
is applied to several real world problems that are commonly
faced by IS programmers. This book covers such topics as
Kohonen neural networks, multi layer neural networks, training,
back propagation, and many other topics.

Neuroph is lightweight Java neural network framework to
develop common neural network architectures. It contains
well designed, open source Java library with small number
of basic classes which correspond to basic NN concepts.
Also has nice GUI neural network editor to quickly create
Java neural network components. It has been released as
open source under the LGPL license, and it's FREE for
you to use it.